Index

A note on the digital index

A link in an index entry is displayed as the section title in which that entry appears. Because some sections have multiple index markers, it is not unusual for an entry to have several links to the same section. Clicking on any link will take you directly to the place in the text in which the marker appears.

Symbols

"%mut%"() function, Extended Example: A Class for Storing Upper-Triangular Matrices

+ operator, Vector Arithmetic and Logical Operations

.libpaths() function, Package Basics

.libPaths() function, Package Basics

.Rdata file, Startup and Shutdown, Startup and Shutdown

.Rhistory file, Startup and Shutdown, Startup and Shutdown

.Rprofile file, Extended Example: Regression Analysis of Exam Grades, Extended Example: Regression Analysis of Exam Grades

== operator, Extended Example: Recoding an Abalone Data Set

> operator, Vectorized Operations

A

abalone data set, Extended Example: A Measure of Association, Extended Example: Recoding an Abalone Data Set, Extended Example: Back to the Abalone Data

recoding, Extended Example: A Measure of Association

using lapply() function, Extended Example: Back to the Abalone Data

abline() graphics function, Functions Are Objects

abs() math function, Doing Math and Simulations in R

accessing, Extended Example: Text Concordance, Creating Data Frames, Creating Data Frames, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function, Extended Example: Reading PUMS Census Files, Accessing the Internet, Overview of TCP/IP, Overview of TCP/IP, Sockets in R

data frames, Creating Data Frames

files on remote machines via URLs, Extended Example: Reading PUMS Census Files

Internet, Accessing the Internet, Overview of TCP/IP, Overview of TCP/IP, Sockets in R

implementing parallel R example, Sockets in R

sockets, Overview of TCP/IP

TCP/IP, Overview of TCP/IP

keyboard and monitor, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function

using print() function, Using the scan() Function

using readline() function, Using the scan() Function

using scan() function, Accessing the Keyboard and Monitor

list components and values, Extended Example: Text Concordance

actual argument, Introduction to Functions

adding, Extended Example: Finding Outliers, Adding and Deleting List Elements, Adding Lines: The abline() Function, Extended Example: More on the Polynomial Regression Example, Adding Points: The points() Function, Adding Points: The points() Function, Adding Points: The points() Function

legends to graphs with legend() function, Adding Points: The points() Function

lines with abline() function, Adding Lines: The abline() Function

list elements, Adding and Deleting List Elements

matrix rows and columns, Extended Example: Finding Outliers

points to graphs with points() function, Extended Example: More on the Polynomial Regression Example

text to graphs with text() function, Adding Points: The points() Function

addmargins() function, Matrix/Array-Like Operations on Tables

adjacency matrix, The Mutual Outlinks Problem

aggregate() function, Extended Example: Finding the Largest Cells in a Table

all() function, Using all() and any()

analogous operations, resizing matrices, Changing the Size of a Matrix

anonymous functions, Extended Example: Back to the Abalone Data, The edit() Function

antibugging, Antibugging

any() function, Using all() and any()

application-specific functions, Extended Example: Discrete-Event Simulation in R

apply() function, Extended Example: Generating a Covariance Matrix, Extended Example: Generating a Covariance Matrix, Using the rbind() and cbind() Functions and Alternatives, Matrix/Array-Like Operations on Tables

applying functions to matrix rows and columns, Extended Example: Generating a Covariance Matrix

matrix-like operations, Using the rbind() and cbind() Functions and Alternatives

obtaining variable marginal values, Matrix/Array-Like Operations on Tables

arguments. See also specific argument by name, Introduction to Functions, Introduction to Functions, Introduction to Functions, Default Arguments, Arithmetic and Boolean Operators and Values

actual, Introduction to Functions

default, Default Arguments

default values for, Arithmetic and Boolean Operators and Values

formal, Introduction to Functions

arithmetic operations, Recycling, Arithmetic and Boolean Operators and Values

array() function, Extended Example: Extracting a Subtable

arrays, Matrices and Arrays as Vectors, Naming Matrix Rows and Columns, Higher-Dimensional Arrays

as vectors, Matrices and Arrays as Vectors

higher-dimensional arrays, Naming Matrix Rows and Columns

as.matrix() function, Avoiding Unintended Dimension Reduction

aspell() function, Finding the Implementations of Generic Methods

assign() function, Extended Example: A Salary Study, Extended Example: A Salary Study, Writing to Nonlocals with assign()

variables, Extended Example: A Salary Study

writing nonlocals with, Writing to Nonlocals with assign()

atomic pragma, OpenMP Code Analysis

atomic vectors, Lists

attr() function, Finding the Implementations of Generic Methods

B

batch mode, Getting Started, Interactive Mode, Help for Other Topics

help feature, Help for Other Topics

running R in, Interactive Mode

Bernoulli sequence, Simulation Programming in R

biglm package, Chunking

bigmemory package, Chunking

binary files, Reading Text Files

binary search tree, Extended Example: A Binary Search Tree

body() function, Returning Complex Objects, Functions Are Objects

Boolean operators, Arithmetic and Boolean Operators and Values

braces, if-else

brackets, List Indexing

Bravington, Mark, Debugging Finding City Pairs

break statement, Loops

breakpoints, setting, Using Browser Commands, Using Browser Commands, Calling browser() Directly

calling browser() function directly, Using Browser Commands

using setbreakpoint() function, Calling browser() Directly

breaks component, hist() function, Lists

browser commands, Using Browser Commands

browser() function, Why Use a Debugging Tool?, Using Browser Commands, Calling browser() Directly

setting breakpoints, Calling browser() Directly

single-stepping through code, Why Use a Debugging Tool?

by() function, The split() Function

byrow argument, matrix() function, Creating Matrices, Reading a Data Frame or Matrix from a File

byte code compilation, Byte Code Compilation

C

c %in% y set operation, Set Operations

c browser command, Using Browser Commands

c() function, Vector Element Names

C-style looping, Loops

cache, Shared-Memory Machines

calculus, Calculus

categorical variables, Factors and Tables

cbind() function, Matrices, Changing the Size of a Matrix, More on Treatment of NA Values

cdf (cumulative distribution function), Calculus

ceiling() math function, Math Functions

cell counts, changing to proportions, Working with Tables

cex option, changing graph character sizes with, Pinpointing Locations: The locator() Function

Chambers, John, Implementing a Generic Function on an S4 Class

character strings, Character Strings, String Manipulation, An Overview of String-Manipulation Functions, grep(), grep(), nchar(), paste(), paste(), paste(), paste(), Regular Expressions, Regular Expressions, Regular Expressions, Extended Example: Testing a Filename for a Given Suffix, Extended Example: Forming Filenames

defined, Character Strings

regular expressions, Regular Expressions, Regular Expressions, Extended Example: Testing a Filename for a Given Suffix

forming filenames example, Extended Example: Testing a Filename for a Given Suffix

testing filename for given suffix example, Regular Expressions

string-manipulation functions, An Overview of String-Manipulation Functions, grep(), grep(), nchar(), paste(), paste(), paste(), paste(), Regular Expressions

gregexpr(), Regular Expressions

grep(), grep()

nchar(), nchar()

paste(), grep()

regexpr(), paste()

sprintf(), paste()

strsplit(), paste()

substr(), paste()

use of string utilities in edtdbg debugging tool, Extended Example: Forming Filenames

chi-square distribution, Functions for Statistical Distributions

child nodes, binary search tree, A Quicksort Implementation

Chinese dialects, aids for learning, Extended Example: Applying Logistic Regression Models

chol() linear algebra function, Linear Algebra Operations on Vectors and Matrices

choose() set operation, Set Operations

chunking memory, Byte Code Compilation

class() function, Finding the Implementations of Generic Methods

cleaner code, When Should You Use Global Variables?

client/server model, Overview of TCP/IP

closures, Functions Are Objects, When Should You Use Global Variables?

cloud() function, Creating Three-Dimensional Plots

cluster, snow package, Introducing the snow Package

clusterApply() function, snow package, Using the apply() Function, Analyzing the snow Code, Extended Example: K-Means Clustering

code files, Interactive Mode

code safety, Vector In, Vector Out

col() function, Filtering on Matrices

: (colon operator), Vector Indexing

colon operator (:), Vector Indexing

color images, Matrix Indexing

column-major order, matrix storage, Matrices and Arrays, Creating Matrices

combinatorial simulation, Built-In Random Variate Generators

combn() function, Set Operations

comdat$countabsamecomm component, Extended Example: A Combinatorial Simulation

comdat$numabchosen component, Extended Example: A Combinatorial Simulation

comdat$whosleft component, Extended Example: A Combinatorial Simulation

comma-separated value (CSV) files, Extended Example: Regression Analysis of Exam Grades Continued

comments, Batch Mode

complete.cases() function, More on Treatment of NA Values

Comprehensive R Archive Network (CRAN), Help on the Internet, Calculus, Downloading R from CRAN

computed mean, saving in variable, A First R Session

concatenating, vectors, A First R Session

connections, Reading Text Files

constructors, Extended Example: A Class for Storing Upper-Triangular Matrices

contingency tables, Working with Tables, “What Is This?”

control statements, Control Statements, Loops, Looping Over Nonvector Sets, Looping Over Nonvector Sets

if-else function, Looping Over Nonvector Sets

looping over nonvector sets, Looping Over Nonvector Sets

loops, Loops

copy-on-change policy, Functional Programming and Memory Issues

cos() math function, Math Functions

counter() function, Closures

counts component, Lists, Lists, Extended Example: Aids for Learning Chinese Dialects

hist() function, Lists

mapsound() function, Extended Example: Aids for Learning Chinese Dialects

covariance matrix, generating, Filtering on Matrices

CRAN (Comprehensive R Archive Network), Help for Other Topics, Calculus, Installing R

critical section, OpenMP, Other OpenMP Pragmas

cross-validation, Extended Example: A Procedure for Polynomial Regression, Extended Example: A Procedure for Polynomial Regression

crossprod() function, Sorting

CSV (comma-separated value) files, Accessing Data Frames

ct.dat file, Working with Tables

cumprod() math function, Math Functions, Extended Example: Calculating a Probability

cumsum() math function, Extended Example: Predicting Discrete-Valued Time Series, Math Functions

cumulative distribution function (cdf), Functions for Statistical Distributions

cumulative sums and products, Cumulative Sums and Products

curve() function, Graphing Explicit Functions

customizing graphs, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Changing Character Sizes: The cex Option, Adding a Polygon: The polygon() Function, Smoothing Points: The lowess() and loess() Functions, Smoothing Points: The lowess() and loess() Functions, Graphing Explicit Functions

adding polygons with polygon() function, Adding a Polygon: The polygon() Function

changing character sizes with cex option, Pinpointing Locations: The locator() Function

changing ranges of axes with xlim and ylim options, Changing Character Sizes: The cex Option

graphing explicit functions, Smoothing Points: The lowess() and loess() Functions

magnifying portions of curve example, Graphing Explicit Functions

smoothing points with lowess() and loess() functions, Smoothing Points: The lowess() and loess() Functions

cut() function, Extended Example: Finding the Largest Cells in a Table

D

data argument, array() function, Extended Example: Extracting a Subtable

data frames, Data Frames, Data Frames, Creating Data Frames, Accessing Data Frames, Other Matrix-Like Operations, Other Matrix-Like Operations, More on Treatment of NA Values, More on Treatment of NA Values, Using the rbind() and cbind() Functions and Alternatives, Extended Example: A Salary Study, Extended Example: A Salary Study, Merging Data Frames, Extended Example: An Employee Database, Extended Example: An Employee Database, Using lapply() and sapply() on Data Frames, Extended Example: Applying Logistic Regression Models, Reading a Data Frame or Matrix from a File

accessing, Creating Data Frames

applying functions to, Extended Example: An Employee Database, Extended Example: An Employee Database, Using lapply() and sapply() on Data Frames, Extended Example: Applying Logistic Regression Models

aids for learning Chinese dialects example, Extended Example: Applying Logistic Regression Models

applying logistic regression models example, Using lapply() and sapply() on Data Frames

using lapply() and sapply() on data frames, Extended Example: An Employee Database

matrix-like operations, Other Matrix-Like Operations, Other Matrix-Like Operations, More on Treatment of NA Values, More on Treatment of NA Values, Using the rbind() and cbind() Functions and Alternatives, Extended Example: A Salary Study

apply() function, Using the rbind() and cbind() Functions and Alternatives

extracting subdata frames, Other Matrix-Like Operations

NA values, More on Treatment of NA Values

rbind() and cbind() functions, More on Treatment of NA Values

salary study example, Extended Example: A Salary Study

merging, Extended Example: A Salary Study, Merging Data Frames

employee database example, Merging Data Frames

reading from files, Reading a Data Frame or Matrix from a File

regression analysis of exam grades example, Accessing Data Frames

data structures, Preview of Some Important R Data Structures, Vectors, the R Workhorse, Character Strings, Character Strings, Matrices, Data Frames, Classes

character strings, Character Strings

classes, Classes

data frames, Data Frames

lists, Matrices

matrices, Character Strings

vectors, Vectors, the R Workhorse

debug package, Debugging Finding City Pairs

debug() function, Why Use a Debugging Tool?

debugger() function, performing checks after crash with, Tracking with the trace() Function

debugging, When Should You Use Global Variables?, Debugging, Debugging, The Essence of Debugging: The Principle of Confirmation, The Essence of Debugging: The Principle of Confirmation, The Essence of Debugging: The Principle of Confirmation, Antibugging, Antibugging, Why Use a Debugging Tool?, Using R Debugging Facilities, Using Browser Commands, Calling browser() Directly, Tracking with the trace() Function, Tracking with the trace() Function, Performing Checks After a Crash with the traceback() and debugger() Function, Moving Up in the World: More Convenient Debugging Tools, Moving Up in the World: More Convenient Debugging Tools, Syntax and Runtime Errors, Syntax and Runtime Errors, Debugging Parallel R Code

ensuring consistency in debugging simulation code, Moving Up in the World: More Convenient Debugging Tools

facilities, Why Use a Debugging Tool?, Using R Debugging Facilities, Using Browser Commands, Calling browser() Directly, Tracking with the trace() Function, Tracking with the trace() Function, Performing Checks After a Crash with the traceback() and debugger() Function

browser commands, Using Browser Commands

debug() and browser() functions, Why Use a Debugging Tool?

debugging sessions, Performing Checks After a Crash with the traceback() and debugger() Function

setting breakpoints, Calling browser() Directly

trace() function, Tracking with the trace() Function

traceback() and debugger() functions, Tracking with the trace() Function

global variables and, When Should You Use Global Variables?

parallel R, Debugging Parallel R Code

principles of, Debugging, The Essence of Debugging: The Principle of Confirmation, The Essence of Debugging: The Principle of Confirmation, The Essence of Debugging: The Principle of Confirmation, Antibugging

antibugging, Antibugging

confirmation, The Essence of Debugging: The Principle of Confirmation

modular, top-down manner, The Essence of Debugging: The Principle of Confirmation

starting small, The Essence of Debugging: The Principle of Confirmation

running GDB on R, Syntax and Runtime Errors

syntax and runtime errors, Syntax and Runtime Errors

tools, Antibugging, Moving Up in the World: More Convenient Debugging Tools

declarations, Matrices and Arrays as Vectors

default arguments, Default Arguments

deleting, Extended Example: Finding Outliers, Adding and Deleting List Elements, Adding and Deleting List Elements, Extended Example: A Binary Search Tree

a node from binary search tree, Extended Example: A Binary Search Tree

list elements, Adding and Deleting List Elements

matrix rows and columns, Extended Example: Finding Outliers

density estimates, same graph, Adding Lines: The abline() Function

DES (discrete-event simulation), writing, Extended Example: Discrete-Event Simulation in R

det() linear algebra function, Linear Algebra Operations on Vectors and Matrices

dev.off() function, Interactive Mode

df parameter, mapsound() function, Extended Example: Aids for Learning Chinese Dialects

dgbsendeditcmd() function, Extended Example: Forming Filenames

diag() linear algebra function, Linear Algebra Operations on Vectors and Matrices

diff() function, Extended Example: A Measure of Association

dim argument, array() function, Extended Example: Extracting a Subtable

dim attribute, matrix class, More on the Vector/Matrix Distinction

dim() function, More on the Vector/Matrix Distinction

dimcode argument, apply() function, Extended Example: Generating a Covariance Matrix

dimension reduction, avoiding, Avoiding Unintended Dimension Reduction

dimnames argument, array() function, Extended Example: Extracting a Subtable

dimnames() function, Matrix/Array-Like Operations on Tables

dir() function, Writing to a File

discrete-event simulation (DES), writing, Extended Example: Discrete-Event Simulation in R

discrete-valued time series, predicting, Extended Example: Finding Runs of Consecutive Ones

do.call() function, Extended Example: Extracting a Subtable

dosim() function, Extended Example: Discrete-Event Simulation in R

double brackets, List Indexing

drop argument, Filtering on Matrices, Avoiding Unintended Dimension Reduction

dtdbg debugging tool, use of string utilities in, Extended Example: Forming Filenames

dual-core machines, Using Multicore Machines

duplicate() function, Copy-on-Change Issues

dynamic task assignment, Embarrassingly Parallel Applications and Those That Aren’t

E

each argument, rep() function, Generating Vector Sequences with seq()

edit() function, Functions Are Objects, Extended Example: A Self-Bookkeeping Vector Class

edtdbg package, Debugging Finding City Pairs

eigen() function, Linear Algebra Operations on Vectors and Matrices, Extended Example: Finding Stationary Distributions of Markovv Chains

eigenvalues, Extended Example: Finding Stationary Distributions of Markovv Chains

eigenvectors, Extended Example: Finding Stationary Distributions of Markovv Chains

elements, Scalars, Vectors, Arrays, and Matrices, Scalars, Vectors, Arrays, and Matrices, Vector Element Names, List Indexing, Adding and Deleting List Elements

list, adding and deleting, List Indexing

vectors, Scalars, Vectors, Arrays, and Matrices, Scalars, Vectors, Arrays, and Matrices, Vector Element Names

adding and deleting, Scalars, Vectors, Arrays, and Matrices

naming, Vector Element Names

embarrassingly parallel applications, Networked Systems of Computers, Embarrassingly Parallel Applications and Those That Aren’t, Static Versus Dynamic Task Assignment

defined, Networked Systems of Computers

turning general problems into, Static Versus Dynamic Task Assignment

employee database example, Merging Data Frames

encapsulation, Object-Oriented Programming

end of file (EOF), Introduction to Connections

envir argument, The Scope Hierarchy, Extended Example: A Function to Display the Contents of a Call Frame, Extended Example: A Function to Display the Contents of a Call Frame

get() function, Extended Example: A Function to Display the Contents of a Call Frame

ls() function, The Scope Hierarchy

environment and scope, Functions Are Objects, The Top-Level Environment, The Top-Level Environment, The Scope Hierarchy, More on ls(), Functions Have (Almost) No Side Effects

function to display contents of call frame example, Functions Have (Almost) No Side Effects

functions have (almost) no side effects, More on ls()

ls() function, The Scope Hierarchy

scope hierarchy, The Top-Level Environment

top-level environment, The Top-Level Environment

EOF (end of file), Introduction to Connections

ess-tracebug package, Debugging Finding City Pairs

event list, DES, Extended Example: Discrete-Event Simulation in R

event-oriented paradigm, Extended Example: Discrete-Event Simulation in R

example() function, The help() Function

exists() function, “What Is This?”

exp() math function, Doing Math and Simulations in R

expandut() function, Extended Example: A Class for Storing Upper-Triangular Matrices

explicit functions, graphing, Smoothing Points: The lowess() and loess() Functions

extracting, Other Matrix-Like Operations, Other Matrix-Like Operations, Matrix/Array-Like Operations on Tables

subdata frames, Other Matrix-Like Operations

subtables, Matrix/Array-Like Operations on Tables

F

f argument, apply() function, Extended Example: Generating a Covariance Matrix

factorial() math function, Math Functions

factors, Factors and Tables, Factors and Tables, Common Functions Used with Factors, The tapply() Function, The split() Function, The split() Function, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table, Other Factor- and Table-Related Functions

functions, Common Functions Used with Factors, The tapply() Function, The split() Function, The split() Function, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table, Other Factor- and Table-Related Functions

aggregate(), Extended Example: Finding the Largest Cells in a Table

by(), The split() Function

cut(), Extended Example: Finding the Largest Cells in a Table

split(), The split() Function

tapply(), The tapply() Function

levels and, Factors and Tables

fangyan, Extended Example: Aids for Learning Chinese Dialects

fargs argument, apply() function, Extended Example: Generating a Covariance Matrix

Fedora, installing R on, Installing R

file.exists() function, Writing to a File

file.info() function, Writing to a File, Extended Example: Sum the Contents of Many Files

filetype criterion, Google, Help for Other Topics

filter() function, Extended Example: Prediction of Discrete-Valued Time Series

filtering, Vectors, Filtering, Filtering, Generating Filtering Indices, Generating Filtering Indices, Filtering on Matrices

defined, Vectors

generating filtering indices, Filtering

matrices, Filtering on Matrices

with subset() function, Generating Filtering Indices

with which() selection function, Generating Filtering Indices

findud() function, Extended Example: A Measure of Association

findwords() function, Adding and Deleting List Elements

first-class objects, Functions Are Objects

floor() math function, Math Functions

for loop, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Vectorization for Speedup, Extended Example: Generating a Powers Matrix

achieving better speed in Monte Carlo simulation example, Vectorization for Speedup

generating powers matrix example, Extended Example: Generating a Powers Matrix

vectorization for speedup, Performance Enhancement: Speed and Memory

formal parameters, Introduction to Functions, Extended Example: Aids for Learning Chinese Dialects, Extended Example: Aids for Learning Chinese Dialects

mapsound() function, Extended Example: Aids for Learning Chinese Dialects

oddcount() function, Introduction to Functions

formals() function, Returning Complex Objects, Functions Are Objects

forming filenames, Extended Example: Testing a Filename for a Given Suffix

four-element vector, adding element to, Scalars, Vectors, Arrays, and Matrices

fromcol parameter, mapsound() function, Extended Example: Aids for Learning Chinese Dialects

functional programming, Why Use R for Your Statistical Work?, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Copy-on-Change Issues

avoiding memory copy example, Copy-on-Change Issues

copy-on-change issues, Functional Programming and Memory Issues

vector assignment issues, Functional Programming and Memory Issues

functions, Introduction to Functions, Introduction to Functions, Default Arguments, Extended Example: Finding Runs of Consecutive Ones, Vector In, Vector Out, Extended Example: Generating a Covariance Matrix, Extended Example: Generating a Covariance Matrix, Using the apply() Function, Accessing List Components and Values, Accessing List Components and Values, Accessing List Components and Values, Extended Example: Back to the Abalone Data, Extended Example: An Employee Database, Extended Example: An Employee Database, Using lapply() and sapply() on Data Frames, Extended Example: Applying Logistic Regression Models, Returning Complex Objects, Extended Example: A Binary Search Tree, The edit() Function, Calculus, Extended Example: Achieving Better Speed in a Monte Carlo Simulation, Installing Packages Manually

anonymous, The edit() Function

applying to data frames, Extended Example: An Employee Database, Extended Example: An Employee Database, Using lapply() and sapply() on Data Frames, Extended Example: Applying Logistic Regression Models

aids for learning Chinese dialects example, Extended Example: Applying Logistic Regression Models

applying logistic regression models example, Using lapply() and sapply() on Data Frames

using lapply() and sapply() functions, Extended Example: An Employee Database

applying to lists, Accessing List Components and Values, Accessing List Components and Values, Accessing List Components and Values, Extended Example: Back to the Abalone Data

abalone data example, Extended Example: Back to the Abalone Data

lapply() and sapply()functions, Accessing List Components and Values

text concordance example, Accessing List Components and Values

applying to matrix rows and columns, Extended Example: Generating a Covariance Matrix, Extended Example: Generating a Covariance Matrix, Using the apply() Function

apply() function, Extended Example: Generating a Covariance Matrix

finding outliers example, Using the apply() Function

as objects, Returning Complex Objects

default arguments, Default Arguments

for statistical distributions, Calculus

listing in packages, Installing Packages Manually

replacement, Extended Example: A Binary Search Tree

transcendental, Vector In, Vector Out

variable scope, Introduction to Functions

vector, Extended Example: Finding Runs of Consecutive Ones, Extended Example: Achieving Better Speed in a Monte Carlo Simulation

G

GCC, Compiling and Running Code

GDB (GNU debugger), Why Use a Debugging Tool?, Debugging R/C Code

general-purpose editors, Text Editors and Integrated Development Environments

generating, Filtering, Filtering on Matrices, Filtering on Matrices, Extended Example: Generating a Powers Matrix

covariance matrices, Filtering on Matrices

filtering indices, Filtering

powers matrices, Extended Example: Generating a Powers Matrix

generic functions, Why Use R for Your Statistical Work?, Classes, Writing S4 Classes

classes, Classes

implementing on S4 classes, Writing S4 Classes

get() function, Loops, Extended Example: A Function to Display the Contents of a Call Frame

looping over nonvector sets, Loops

getAnywhere() function, Finding the Implementations of Generic Methods

getnextevnt() function, Extended Example: Discrete-Event Simulation in R

getwd() function, Writing to a File

global variables, Introduction to Functions, When Should You Use Global Variables?

GNU debugger (GDB), Why Use a Debugging Tool?, Debugging R/C Code

GNU S language, Introduction

GPU programming, Extended Example: Discrete-Event Simulation in R, GPU Programming

GPUs (graphics processing units), The omp single Pragma

gputools package, The omp single Pragma

granularity, Embarrassingly Parallel Applications and Those That Aren’t

graphical user interfaces (GUIs), Why Use R for Your Statistical Work?

graphics processing units (GPUs), GPU Programming

graphs, Creating Graphs, The Workhorse of R Base Graphics: The plot() Function, Adding Lines: The abline() Function, Adding Lines: The abline() Function, Adding Lines: The abline() Function, Extended Example: Two Density Estimates on the Same Graph, Extended Example: More on the Polynomial Regression Example, Adding Points: The points() Function, Adding Points: The points() Function, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Changing Character Sizes: The cex Option, Adding a Polygon: The polygon() Function, Smoothing Points: The lowess() and loess() Functions, Smoothing Points: The lowess() and loess() Functions, Graphing Explicit Functions, Saving Graphs to Files, Creating Three-Dimensional Plots

customizing, Adding Lines: The abline() Function, Extended Example: More on the Polynomial Regression Example, Adding Points: The points() Function, Adding Points: The points() Function, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Changing Character Sizes: The cex Option, Adding a Polygon: The polygon() Function, Smoothing Points: The lowess() and loess() Functions, Smoothing Points: The lowess() and loess() Functions, Graphing Explicit Functions

adding legends with legend() function, Adding Points: The points() Function

adding lines with abline() function, Adding Lines: The abline() Function

adding points with points() function, Extended Example: More on the Polynomial Regression Example

adding polygons with polygon() function, Adding a Polygon: The polygon() Function

adding text with text() function, Adding Points: The points() Function

changing character sizes with cex option, Pinpointing Locations: The locator() Function

changing ranges of axes with xlim and ylim options, Changing Character Sizes: The cex Option

graphing explicit functions, Smoothing Points: The lowess() and loess() Functions

magnifying portions of curve example, Graphing Explicit Functions

smoothing points with lowess() and loess() functions, Smoothing Points: The lowess() and loess() Functions

pinpointing locations with locator() function, Pinpointing Locations: The locator() Function

plot() function, The Workhorse of R Base Graphics: The plot() Function

plots, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Creating Three-Dimensional Plots

restoring, Pinpointing Locations: The locator() Function

three-dimensional, Creating Three-Dimensional Plots

polynomial regression example, Extended Example: Two Density Estimates on the Same Graph

saving to files, Saving Graphs to Files

starting new graph while keeping old, Adding Lines: The abline() Function

two density estimates on same graph example, Adding Lines: The abline() Function

grayscale images, Matrix Indexing

gregexpr() function, regexpr()

grep() function, Extended Example: A Salary Study, grep()

GUIs (graphical user interfaces), Why Use R for Your Statistical Work?

H

hard drive, loading packages from, Package Basics

help feature, Startup and Shutdown, Startup and Shutdown, The help() Function, The example() Function, If You Don’t Know Quite What You’re Looking For, Help for Other Topics, Help for Other Topics

additional topics, If You Don’t Know Quite What You’re Looking For

batch mode, Help for Other Topics

example() function, The help() Function

help() function, Startup and Shutdown

help.search() function, The example() Function

online, Help for Other Topics

help() function, Startup and Shutdown

help.search() function, The example() Function

higher-dimensional arrays, Naming Matrix Rows and Columns

hist() function, Interactive Mode, Lists

hosts, The omp single Pragma

Huang, Min-Yu, Writing C/C++ Functions to Be Called from R

I

I/O (input/output), Input/Output, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function, Printing to the Screen, Reading a Data Frame or Matrix from a File, Reading Text Files, Reading Text Files, Extended Example: Reading PUMS Census Files, Extended Example: Reading PUMS Census Files, Writing to a File, Writing to a File, Writing to a File, Writing to a File, Extended Example: Sum the Contents of Many Files, Overview of TCP/IP, Overview of TCP/IP, Sockets in R

accessing Internet, Extended Example: Sum the Contents of Many Files, Overview of TCP/IP, Overview of TCP/IP, Sockets in R

implementing parallel R example, Sockets in R

sockets in R, Overview of TCP/IP

TCP/IP, Overview of TCP/IP

accessing keyboard and monitor, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function

using print() function, Using the scan() Function

using readline() function, Using the scan() Function

using scan() function, Accessing the Keyboard and Monitor

reading files, Printing to the Screen, Reading a Data Frame or Matrix from a File, Reading Text Files, Reading Text Files, Extended Example: Reading PUMS Census Files, Extended Example: Reading PUMS Census Files

accessing files on remote machines via URLs, Extended Example: Reading PUMS Census Files

connections, Reading Text Files

reading data frame or matrix from files, Reading a Data Frame or Matrix from a File

reading PUMS census files example, Extended Example: Reading PUMS Census Files

reading text files, Reading Text Files

writing files, Writing to a File, Writing to a File, Writing to a File, Writing to a File

getting files and directory information, Writing to a File

sum contents of many files example, Writing to a File

writing to files, Writing to a File

identical() function, Testing Vector Equality

IDEs (integrated development environments), Why Use R for Your Statistical Work?, Extended Example: A Self-Bookkeeping Vector Class

if statements, nested, Loops

ifelse() function, The Selection Function which(), A Vectorized if-then-else: The ifelse() Function, Extended Example: A Measure of Association, Looping Over Nonvector Sets

assessing statistical relation of two variables example, A Vectorized if-then-else: The ifelse() Function

control statements, Looping Over Nonvector Sets

recoding abalone data set example, Extended Example: A Measure of Association

image manipulation, Matrix Indexing

images component, mapsound() function, Extended Example: Aids for Learning Chinese Dialects

immutable objects, Functional Programming and Memory Issues

indexing, Vector Arithmetic and Logical Operations, Matrix Indexing, Creating Lists, Creating Lists

list, Creating Lists

matrices, Matrix Indexing

vector, Vector Arithmetic and Logical Operations

indices, filtering, Filtering

inheritance, Object-Oriented Programming, Object-Oriented Programming, Using Inheritance

defined, Object-Oriented Programming

S3 classes, Using Inheritance

initglbls() function, Extended Example: Discrete-Event Simulation in R

input/output (I/O). See I/O, Installing R

installing packages. See packages, Installing R

installing R, Installing R, Installing R, Installing R, Installing from a Linux Package Manager

downloading base package from CRAN, Installing R

from Linux package manager, Installing R

from source, Installing from a Linux Package Manager

install_packages() function, Package Basics

integrated development environments (IDEs), Why Use R for Your Statistical Work?, Extended Example: A Self-Bookkeeping Vector Class

intensity, pixel, Matrix Indexing

interactive mode, How to Run R

interfacing R to other languages, Interfacing R to Other Languages, Interfacing R to Other Languages, Writing C/C++ Functions to Be Called from R, Example: Extracting Subdiagonals from a Square Matrix, Debugging R/C Code, Debugging R/C Code, Extended Example: Prediction of Discrete-Valued Time Series

using R from Python, Extended Example: Prediction of Discrete-Valued Time Series

writing C/C++ functions to be called from R, Interfacing R to Other Languages, Writing C/C++ Functions to Be Called from R, Example: Extracting Subdiagonals from a Square Matrix, Debugging R/C Code, Debugging R/C Code

compiling and running code, Example: Extracting Subdiagonals from a Square Matrix

debugging R/C code, Debugging R/C Code

extracting subdiagonals from square matrix example, Writing C/C++ Functions to Be Called from R

prediction of discrete-valued time series example, Debugging R/C Code

internal data sets, A First R Session

internal storage, matrix, Matrices and Arrays, Creating Matrices

Internet Protocol (IP) address, Overview of TCP/IP

Internet, accessing, Extended Example: Sum the Contents of Many Files, Overview of TCP/IP, Overview of TCP/IP, Sockets in R

implementing parallel R example, Sockets in R

sockets, Overview of TCP/IP

TCP/IP, Overview of TCP/IP

intersect() set operation, Set Operations

intextract() function, Extended Example: Reading PUMS Census Files

IP (Internet Protocol) address, Overview of TCP/IP

J

join operation, Extended Example: A Salary Study

K

keyboard, accessing, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function

printing to screen, Using the scan() Function

using readline() function, Using the scan() Function

using scan() function, Accessing the Keyboard and Monitor

KMC (k-means clustering), How Much Speedup Can Be Attained?

L

lag operations, vector, Extended Example: A Measure of Association

lapply() function, Extended Example: A Measure of Association, Accessing List Components and Values, Applying Functions to Lists, Extended Example: An Employee Database, Loops

applying functions to lists, Applying Functions to Lists

lists, Extended Example: A Measure of Association

looping over nonvector sets, Loops

using on data frames, Extended Example: An Employee Database

latency, Shared-Memory Machines

lazy evaluation principle, Extended Example: Recoding an Abalone Data Set, Default Values for Arguments

leaving-one-out method, Extended Example: A Procedure for Polynomial Regression, Extended Example: A Procedure for Polynomial Regression

legend() function, Adding Points: The points() Function

length() function, Obtaining the Length of a Vector, Obtaining the Length of a Vector, Vector Indexing

obtaining length of vector, Obtaining the Length of a Vector

vector indexing, Vector Indexing

levels, factors and, Factors and Tables

library functions, Extended Example: Discrete-Event Simulation in R

linear algebra operations, on vectors and matrices, Creating Matrices, Sorting, Linear Algebra Operations on Vectors and Matrices, Extended Example: Vector Cross Product

finding stationary distributions of Markov chains example, Extended Example: Vector Cross Product

vector cross product example, Linear Algebra Operations on Vectors and Matrices

lines() function, Adding Lines: The abline() Function

Linux package manager, installing R from, Installing R

lists, Matrices, Lists, Creating Lists, Creating Lists, Adding and Deleting List Elements, Adding and Deleting List Elements, Adding and Deleting List Elements, Extended Example: Text Concordance, Accessing List Components and Values, Accessing List Components and Values, Applying Functions to Lists, Extended Example: Back to the Abalone Data, Extended Example: Back to the Abalone Data

accessing components and values, Extended Example: Text Concordance

applying functions to, Accessing List Components and Values, Accessing List Components and Values, Applying Functions to Lists, Extended Example: Back to the Abalone Data

abalone data example, Extended Example: Back to the Abalone Data

lapply() and sapply()functions, Accessing List Components and Values

text concordance example, Accessing List Components and Values

general operations, Creating Lists, Creating Lists, Adding and Deleting List Elements, Adding and Deleting List Elements, Adding and Deleting List Elements

adding and deleting list elements, Adding and Deleting List Elements

getting size of list, Adding and Deleting List Elements

list indexing, Creating Lists

text concordance example, Adding and Deleting List Elements

recursive lists, Extended Example: Back to the Abalone Data

lm()function, Data Frames, Object-Oriented Programming

load balance, Static Versus Dynamic Task Assignment

locator() function, Extended Example: Image Manipulation, Extended Example: Image Manipulation, Pinpointing Locations: The locator() Function

determining relevant rows and columns, Extended Example: Image Manipulation

pinpointing locations with, Pinpointing Locations: The locator() Function

loess() function, Smoothing Points: The lowess() and loess() Functions

log() math function, Doing Math and Simulations in R

log10() math function, Doing Math and Simulations in R

logical operations, Common Vector Operations

logistic regression models, applying, Using lapply() and sapply() on Data Frames

long-run state distribution, Markov modeling, Extended Example: Finding Stationary Distributions of Markovv Chains

loops, control statements, Loops

lowess() function, Smoothing Points: The lowess() and loess() Functions

ls() function, The Scope Hierarchy, The Scope Hierarchy, Implementing a Generic Function on an S4 Class

environment and scope, The Scope Hierarchy

listing objects with, Implementing a Generic Function on an S4 Class

M

m argument, apply() function, Extended Example: Generating a Covariance Matrix

M/M/1 queue, Extended Example: Discrete-Event Simulation in R, Extended Example: Discrete-Event Simulation in R

magnifying portions of curve, Graphing Explicit Functions

makerow() function, Extended Example: Reading PUMS Census Files

managers, snow package, Introducing the snow Package

managing objects, Implementing a Generic Function on an S4 Class, Implementing a Generic Function on an S4 Class, Listing Your Objects with the ls() Function, Removing Specific Objects with the rm() Function, Removing Specific Objects with the rm() Function, “What Is This?”

determining object structure, Removing Specific Objects with the rm() Function

exists() function, “What Is This?”

listing objects with ls()function, Implementing a Generic Function on an S4 Class

removing specific objects with rm() function, Listing Your Objects with the ls() Function

saving collection of objects with save() function, Removing Specific Objects with the rm() Function

mapsound() function, Extended Example: Applying Logistic Regression Models

marginal values, variable, Matrix/Array-Like Operations on Tables

Markov chains, Extended Example: Vector Cross Product

MASS package, If You Don’t Know Quite What You’re Looking For, Package Basics

math functions, Math Functions, Math Functions, Extended Example: Calculating a Probability, Cumulative Sums and Products, Calculus

calculating probability example, Math Functions

calculus, Calculus

cumulative sums and products, Cumulative Sums and Products

minima and maxima, Extended Example: Calculating a Probability

matrices, Character Strings, Matrices and Arrays as Vectors, Matrices and Arrays, Creating Matrices, Creating Matrices, Matrix Indexing, Matrix Indexing, Filtering on Matrices, Filtering on Matrices, Extended Example: Generating a Covariance Matrix, Extended Example: Generating a Covariance Matrix, Using the apply() Function, Extended Example: Finding Outliers, Extended Example: Finding Outliers, Changing the Size of a Matrix, Extended Example: Finding the Closest Pair of Vertices in a Graph, Avoiding Unintended Dimension Reduction, Avoiding Unintended Dimension Reduction, Sorting, Reading a Data Frame or Matrix from a File

adding and deleting rows and columns, Extended Example: Finding Outliers, Extended Example: Finding Outliers, Changing the Size of a Matrix

finding closest pair of vertices in graph example, Changing the Size of a Matrix

resizing matrix, Extended Example: Finding Outliers

applying functions to rows and columns, Extended Example: Generating a Covariance Matrix, Extended Example: Generating a Covariance Matrix, Using the apply() Function

apply() function, Extended Example: Generating a Covariance Matrix

finding outliers example, Using the apply() Function

as vectors, Matrices and Arrays as Vectors

avoiding unintended dimension reduction, Avoiding Unintended Dimension Reduction

linear algebra operations on, Sorting

naming rows and columns, Avoiding Unintended Dimension Reduction

operations, Creating Matrices, Creating Matrices, Matrix Indexing, Matrix Indexing, Filtering on Matrices, Filtering on Matrices

filtering, Filtering on Matrices

generating covariance matrix example, Filtering on Matrices

image manipulation example, Matrix Indexing

linear algebra operations, Creating Matrices

matrix indexing, Matrix Indexing

reading from files, Reading a Data Frame or Matrix from a File

vector/matrix distinction, Extended Example: Finding the Closest Pair of Vertices in a Graph

matrix class, More on the Vector/Matrix Distinction

matrix() function, Creating Matrices

matrix-inverse update method, Extended Example: A Procedure for Polynomial Regression

matrix-like operations, Other Matrix-Like Operations, Other Matrix-Like Operations, More on Treatment of NA Values, More on Treatment of NA Values, Using the rbind() and cbind() Functions and Alternatives, Extended Example: A Salary Study

apply() function, Using the rbind() and cbind() Functions and Alternatives

extracting subdata frames, Other Matrix-Like Operations

NA values, More on Treatment of NA Values

rbind() and cbind() functions, More on Treatment of NA Values

salary study example, Extended Example: A Salary Study

matrix-multiplication operator, Matrices

matrix/array-like operations, Working with Tables

max() math function, Math Functions, Minima and Maxima

maxima function, Extended Example: Calculating a Probability

mean() function, Extended Example: Predicting Discrete-Valued Time Series

memory, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Copy-on-Change Issues, Byte Code Compilation, Byte Code Compilation, Chunking

chunking, Byte Code Compilation

functional programming, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Copy-on-Change Issues

avoiding memory copy example, Copy-on-Change Issues

copy-on-change issues, Functional Programming and Memory Issues

vector assignment issues, Functional Programming and Memory Issues

using R packages for memory management, Chunking

merge sort method, numerical sorting, Networked Systems of Computers

merge() function, Extended Example: A Salary Study

merging data frames, Extended Example: A Salary Study, Merging Data Frames

employee database example, Merging Data Frames

metacharacters, regexpr()

methods() function, Example: OOP in the lm() Linear Model Function

microdata, Extended Example: Reading PUMS Census Files

min() math function, Math Functions, Extended Example: Calculating a Probability

minima function, Extended Example: Calculating a Probability

modes, Getting Started, Getting Started, How to Run R, Interactive Mode, Interactive Mode, Help for Other Topics, Help for Other Topics, Scalars, Vectors, Arrays, and Matrices

batch, Getting Started, Interactive Mode, Help for Other Topics

defined, Scalars, Vectors, Arrays, and Matrices

interactive, How to Run R

modulo operator, Using NULL

monitor, accessing, Accessing the Keyboard and Monitor, Accessing the Keyboard and Monitor, Using the scan() Function, Using the scan() Function

using print() function, Using the scan() Function

using readline() function, Using the scan() Function

using scan() function, Accessing the Keyboard and Monitor

Monte Carlo simulation, achieving better speed in, Vectorization for Speedup

multicore machines, Extended Example: K-Means Clustering

mutlinks() function, Running snow Code

mutual outlinks, Parallel R, Extended Example: Mutual Outlinks Problem in OpenMP

mvrnorm() function, MASS package, If You Don’t Know Quite What You’re Looking For, Package Basics

N

n browser command, Using Browser Commands

NA values, Vector In, Matrix Out, More on Treatment of NA Values, More on Treatment of NA Values

matrix-like operations, More on Treatment of NA Values

vectors, Vector In, Matrix Out

named arguments, Default Values for Arguments

names() function, Vector Element Names

naming, Vector Element Names, Avoiding Unintended Dimension Reduction, Avoiding Unintended Dimension Reduction

matrix rows and columns, Avoiding Unintended Dimension Reduction

vector elements, Vector Element Names

nchar() function, grep()

ncol() function, More on the Vector/Matrix Distinction

negative subscripts, Vector Indexing, Matrix Indexing

network, defined, Overview of TCP/IP

Newton-Raphson method, Minima and Maxima

next statement, Loops

Nile data set, A First R Session

noise, adding to image, Extended Example: Image Manipulation

nominal variables, Factors and Tables

nonlocals, No Pointers in R, No Pointers in R, Writing to Nonlocals with assign()

writing to with superassignment operator, No Pointers in R

writing with assign() function, Writing to Nonlocals with assign()

nonvector sets, looping control statements over, Looping Over Nonvector Sets

nonvisible functions, Finding the Implementations of Generic Methods

nreps values, Built-In Random Variate Generators

nrow() function, More on the Vector/Matrix Distinction

NULL values, Using NULL

O

object-oriented programming. See OOP, Returning Complex Objects

objects. See also managing objects, Returning Complex Objects, Functions Are Objects, Functional Programming and Memory Issues

first-class, Functions Are Objects

immutable, Functional Programming and Memory Issues

oddcount() function, A First R Session, Loops

omp barrier pragma, OpenMP, Other OpenMP Pragmas

omp critical pragma, OpenMP, Other OpenMP Pragmas

omp singlepragma, OpenMP, Other OpenMP Pragmas

OOP (object-oriented programming), Why Use R for Your Statistical Work?, Object-Oriented Programming, Extended Example: A Procedure for Polynomial Regression, Extended Example: A Procedure for Polynomial Regression, Extended Example: A Procedure for Polynomial Regression, S4 Classes, Writing S4 Classes, Implementing a Generic Function on an S4 Class

managing objects. See managing objects, Extended Example: A Procedure for Polynomial Regression

S3 classes. See S3 classes, Extended Example: A Procedure for Polynomial Regression

S4 classes, Extended Example: A Procedure for Polynomial Regression, S4 Classes, Writing S4 Classes, Implementing a Generic Function on an S4 Class

implementing generic function on, Writing S4 Classes

vs. S3 classes, Implementing a Generic Function on an S4 Class

writing, S4 Classes

OpenMP, OpenMP Code Analysis, Other OpenMP Pragmas, Other OpenMP Pragmas, Other OpenMP Pragmas, Other OpenMP Pragmas

code analysis, OpenMP Code Analysis

omp barrier pragma, Other OpenMP Pragmas

omp critical pragma, Other OpenMP Pragmas

omp singlepragma, Other OpenMP Pragmas

operations, Recycling, Common Vector Operations, Vector Arithmetic and Logical Operations, Vector Indexing, Generating Useful Vectors with the : Operator, Generating Vector Sequences with seq(), Vectorized Operations, Vector In, Vector Out, Creating Matrices, Creating Matrices, Matrix Indexing, Matrix Indexing, Filtering on Matrices, Filtering on Matrices, Creating Lists, Creating Lists, Creating Lists, Adding and Deleting List Elements, Adding and Deleting List Elements, Adding and Deleting List Elements, Working with Tables

list, Creating Lists, Creating Lists, Adding and Deleting List Elements, Adding and Deleting List Elements, Adding and Deleting List Elements

adding and deleting list elements, Adding and Deleting List Elements

getting size of list, Adding and Deleting List Elements

list indexing, Creating Lists

text concordance example, Adding and Deleting List Elements

matrix, Creating Matrices, Creating Matrices, Matrix Indexing, Matrix Indexing, Filtering on Matrices, Filtering on Matrices

filtering, Filtering on Matrices

generating covariance matrix example, Filtering on Matrices

image manipulation example, Matrix Indexing

indexing, Matrix Indexing

linear algebra operations, Creating Matrices

matrix/array-like, Working with Tables

vector, Recycling, Common Vector Operations, Vector Arithmetic and Logical Operations, Vector Indexing, Generating Useful Vectors with the : Operator, Generating Vector Sequences with seq(), Vectorized Operations, Vector In, Vector Out

arithmetic and logical operations, Common Vector Operations

colon operator (:), Vector Indexing

generating vector sequences with seq() function, Generating Useful Vectors with the : Operator

repeating vector constants with rep() function, Generating Vector Sequences with seq()

vector in, matrix out, Vector In, Vector Out

vector in, vector out, Vectorized Operations

vector indexing, Vector Arithmetic and Logical Operations

operator precedence, Generating Useful Vectors with the : Operator

order() function, Extended Example: Text Concordance, Continued, Functions for Statistical Distributions

outliers, Extended Example: A Measure of Association

P

packages, Installing and Using Packages, Package Basics, Package Basics, Installing Packages Automatically, Installing Packages Automatically, Installing Packages Manually

installing, Package Basics, Installing Packages Automatically, Installing Packages Automatically

automatically, Installing Packages Automatically

manually, Installing Packages Automatically

listing functions in, Installing Packages Manually

loading from hard drive, Package Basics

parallel R, Sockets in R, Parallel R, Parallel R, The Mutual Outlinks Problem, Introducing the snow Package, Running snow Code, How Much Speedup Can Be Attained?, Extended Example: K-Means Clustering, Extended Example: K-Means Clustering, Extended Example: K-Means Clustering, Extended Example: Mutual Outlinks Problem in OpenMP, Running the OpenMP Code, OpenMP Code Analysis, Other OpenMP Pragmas, GPU Programming, Sources of Overhead, Sources of Overhead, Networked Systems of Computers, Networked Systems of Computers, Embarrassingly Parallel Applications and Those That Aren’t, Static Versus Dynamic Task Assignment, Debugging Parallel R Code

debugging, Networked Systems of Computers, Static Versus Dynamic Task Assignment, Debugging Parallel R Code

embarrassingly parallel applications, Networked Systems of Computers

turning general problems into, Static Versus Dynamic Task Assignment

implementing, Sockets in R

mutual outlinks, Parallel R

resorting to C, Extended Example: K-Means Clustering, Extended Example: K-Means Clustering, Extended Example: Mutual Outlinks Problem in OpenMP, Running the OpenMP Code, OpenMP Code Analysis, Other OpenMP Pragmas, GPU Programming

GPU programming, GPU Programming

multicore machines, Extended Example: K-Means Clustering

mutual outlinks, Extended Example: Mutual Outlinks Problem in OpenMP

OpenMP code analysis, OpenMP Code Analysis

OpenMP pragmas, Other OpenMP Pragmas

running OpenMP code, Running the OpenMP Code

snow package, The Mutual Outlinks Problem, Introducing the snow Package, Running snow Code, How Much Speedup Can Be Attained?, Extended Example: K-Means Clustering

analyzing snow code, Running snow Code

k-means clustering (KMC), Extended Example: K-Means Clustering

running snow code, Introducing the snow Package

speedup, How Much Speedup Can Be Attained?

sources of overhead, Sources of Overhead, Sources of Overhead, Networked Systems of Computers

networked systems of computers, Networked Systems of Computers

shared-memory machines, Sources of Overhead

static vs. dynamic task assignment, Embarrassingly Parallel Applications and Those That Aren’t

parent.frame() function, More on ls()

paste() function, grep(), Extended Example: Forming Filenames, Extended Example: More on the Polynomial Regression Example

PDF devices, saving displayed graphs, R Graphics Devices

pdf() function, Interactive Mode

Pearson product-moment correlation, Extended Example: A Measure of Association

performance enhancement, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Vectorization for Speedup, Extended Example: Generating a Powers Matrix, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Copy-on-Change Issues, Extended Example: Avoiding Memory Copy, Byte Code Compilation, Byte Code Compilation, Chunking

byte code compilation, Byte Code Compilation

chunking, Byte Code Compilation

for loop, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Vectorization for Speedup, Extended Example: Generating a Powers Matrix

achieving better speed in a Monte Carlo simulation example, Vectorization for Speedup

generating powers matrix example, Extended Example: Generating a Powers Matrix

vectorization for speedup, Performance Enhancement: Speed and Memory

functional programming, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Functional Programming and Memory Issues, Copy-on-Change Issues

avoiding memory copy example, Copy-on-Change Issues

copy-on-change issues, Functional Programming and Memory Issues

vector assignment issues, Functional Programming and Memory Issues

using R packages for memory management, Chunking

using Rprof() function to find slow spots in code, Extended Example: Avoiding Memory Copy

writing fast R code, Performance Enhancement: Speed and Memory

Perron-Frobenius theorem, Extended Example: Finding Stationary Distributions of Markovv Chains

persp() function, The example() Function, Creating Three-Dimensional Plots

pixel intensity, Matrix Indexing

plot() function, Why Use R for Your Statistical Work?, Classes, The Workhorse of R Base Graphics: The plot() Function

plots, Pinpointing Locations: The locator() Function, Pinpointing Locations: The locator() Function, Creating Three-Dimensional Plots

restoring, Pinpointing Locations: The locator() Function

three-dimensional, Creating Three-Dimensional Plots

plyr package, Extended Example: Finding the Largest Cells in a Table

pmax() math function, Math Functions, Minima and Maxima

pmf (probability mass function), Calculus

pmin() math function, Math Functions, Extended Example: Calculating a Probability

pointers, Extended Example: A Function to Display the Contents of a Call Frame

points() function, Extended Example: More on the Polynomial Regression Example

polygon() function, Adding a Polygon: The polygon() Function

polymorphism, Why Use R for Your Statistical Work?, Why Use R for Your Statistical Work?, Object-Oriented Programming, Object-Oriented Programming, S3 Classes

defined, Why Use R for Your Statistical Work?, Object-Oriented Programming

generic functions, S3 Classes

polynomial regression, Extended Example: A Class for Storing Upper-Triangular Matrices, Extended Example: Two Density Estimates on the Same Graph

port number, Overview of TCP/IP

powers matrix, generating, Extended Example: Generating a Powers Matrix

pragmas, OpenMP, OpenMP Code Analysis

preda() function, Extended Example: Predicting Discrete-Valued Time Series

principle of confirmation, debugging, Debugging

print() function, Extended Example: Regression Analysis of Exam Grades, Using the scan() Function

print.ut() function, Extended Example: A Class for Storing Upper-Triangular Matrices

prntrslts() function, Extended Example: Discrete-Event Simulation in R

probability mass function (pmf), Functions for Statistical Distributions

probability, calculating, Math Functions

procpairs() function, OpenMP Code Analysis

prod() math function, Math Functions

programming structures. See R programming structures, Extended Example: Reading PUMS Census Files

Public Use Microdata Samples (PUMS) census files, reading, Extended Example: Reading PUMS Census Files

Python, using R from, Extended Example: Prediction of Discrete-Valued Time Series

Q

Q browser command, Using Browser Commands

qr() linear algebra function, Linear Algebra Operations on Vectors and Matrices

Quicksort implementation, Recursion

R

R console, How to Run R

R packages, for memory management, Chunking

R programming structures, R Programming Structures, Control Statements, Loops, Looping Over Nonvector Sets, Looping Over Nonvector Sets, Arithmetic and Boolean Operators and Values, Arithmetic and Boolean Operators and Values, Default Values for Arguments, Return Values, Return Values, Returning Complex Objects, Functions Are Objects, The Top-Level Environment, The Top-Level Environment, The Scope Hierarchy, More on ls(), Functions Have (Almost) No Side Effects, Extended Example: A Function to Display the Contents of a Call Frame, No Pointers in R, No Pointers in R, Writing to Nonlocals with assign(), Extended Example: Discrete-Event Simulation in R, Extended Example: Discrete-Event Simulation in R, When Should You Use Global Variables?, Recursion, Recursion, A Quicksort Implementation, Extended Example: A Binary Search Tree, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, The edit() Function, The edit() Function

anonymous functions, The edit() Function

arithmetic and Boolean operators and values, Arithmetic and Boolean Operators and Values

control statements, Control Statements, Loops, Looping Over Nonvector Sets, Looping Over Nonvector Sets

if-else function, Looping Over Nonvector Sets

looping over nonvector sets, Looping Over Nonvector Sets

loops, Loops

default values for arguments, Arithmetic and Boolean Operators and Values

environment and scope issues, Functions Are Objects, The Top-Level Environment, The Top-Level Environment, The Scope Hierarchy, More on ls(), Functions Have (Almost) No Side Effects

function to display contents of call frame example, Functions Have (Almost) No Side Effects

ls() function, The Scope Hierarchy

scope hierarchy, The Top-Level Environment

side effects, More on ls()

top-level environment, The Top-Level Environment

functions as objects, Returning Complex Objects

pointers, lack of, Extended Example: A Function to Display the Contents of a Call Frame

recursion, Recursion, Recursion, A Quicksort Implementation

binary search tree example, A Quicksort Implementation

Quicksort implementation, Recursion

replacement functions, Extended Example: A Binary Search Tree

return values, Default Values for Arguments, Return Values, Return Values

deciding whether to explicitly call return() function, Return Values

returning complex objects, Return Values

tools for composing function code, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class

edit() function, Extended Example: A Self-Bookkeeping Vector Class

text editors and IDEs, Extended Example: A Self-Bookkeeping Vector Class

writing, No Pointers in R, No Pointers in R, Writing to Nonlocals with assign(), Extended Example: Discrete-Event Simulation in R, Extended Example: Discrete-Event Simulation in R, When Should You Use Global Variables?, The edit() Function

binary operations, The edit() Function

closures, When Should You Use Global Variables?

discrete-event simulation (DES) in R example, Extended Example: Discrete-Event Simulation in R

when to use global variables, Extended Example: Discrete-Event Simulation in R

writing to nonlocals with assign() function, Writing to Nonlocals with assign()

writing to nonlocals with the superassignment operator, No Pointers in R

race condition, OpenMP Code Analysis

random variate generators, Simulation Programming in R

rank() function, Sorting

rbind() function, Matrices, Changing the Size of a Matrix, More on Treatment of NA Values, Extended Example: Discrete-Event Simulation in R

ordering events, Extended Example: Discrete-Event Simulation in R

resizing matrices, Changing the Size of a Matrix

rbinom() function, Simulation Programming in R

Rdsm package, implementing parallel R, Extended Example: Implementing Parallel R

reactevnt() function, Extended Example: Discrete-Event Simulation in R

read.csv() function, Extended Example: A Salary Study

readBin() function, Sockets in R

reading files, Printing to the Screen, Reading a Data Frame or Matrix from a File, Reading Text Files, Reading Text Files, Extended Example: Reading PUMS Census Files, Extended Example: Reading PUMS Census Files

accessing files on remote machines via URLs, Extended Example: Reading PUMS Census Files

connections, Reading Text Files

reading data frames or matrices from files, Reading a Data Frame or Matrix from a File

reading PUMS census files example, Extended Example: Reading PUMS Census Files

reading text files, Reading Text Files

readline() function, Using the scan() Function

readLines() function, Sockets in R

reassigning matrices, Extended Example: Finding Outliers

recursion, Recursion, Recursion, A Quicksort Implementation

binary search tree example, A Quicksort Implementation

Quicksort implementation, Recursion

recursive argument, concatenate function, Recursive Lists

recursive vectors, Creating Lists

recycling, Vectors, Vectors, Recycling

defined, Vectors

vectors, Recycling

reference classes, No Pointers in R

regexpr() function, paste()

regression analysis of exam grades, Classes, Accessing Data Frames

regular expressions, character string manipulation, regexpr()

remote machines, accessing files on, Extended Example: Reading PUMS Census Files

rep() function, repeating vector constants with, Generating Vector Sequences with seq()

repeat loop, Extended Example: Reading PUMS Census Files

repeat statement, Loops

replacement functions, Extended Example: A Binary Search Tree, What’s Considered a Replacement Function?, What’s Considered a Replacement Function?

defined, What’s Considered a Replacement Function?

self-bookkeeping vector class example, What’s Considered a Replacement Function?

reshape package, Extended Example: Finding the Largest Cells in a Table

resizing matrices, Extended Example: Finding Outliers

return statement, Introduction to Functions

return values, Default Values for Arguments, Return Values, Return Values

deciding whether to explicitly call return() function, Return Values

returning complex objects, Return Values

REvolution Analytics, Moving Up in the World: More Convenient Debugging Tools

rexp() function, Simulation Programming in R

Rf_PrintValue(s) function, Running GDB on R Itself

rgamma() function, Simulation Programming in R

rm() function, Listing Your Objects with the ls() Function

rnorm() function, Interactive Mode, Simulation Programming in R

round() function, Vectorized Operations, Math Functions

routers, Overview of TCP/IP

row() function, Filtering on Matrices

rownames() function, Naming Matrix Rows and Columns

rpois() function, Simulation Programming in R

Rprof() function, Extended Example: Avoiding Memory Copy

RPy module, Extended Example: Prediction of Discrete-Valued Time Series, Extended Example: Prediction of Discrete-Valued Time Series, Extended Example: Prediction of Discrete-Valued Time Series

installing, Extended Example: Prediction of Discrete-Valued Time Series

syntax, Extended Example: Prediction of Discrete-Valued Time Series

runif() function, Simulation Programming in R

running, Getting Started, How to Run R, Interactive Mode, A First R Session, Syntax and Runtime Errors, Syntax and Runtime Errors, Introducing the snow Package, Running the OpenMP Code

GDB on R, Syntax and Runtime Errors

OpenMP code, Running the OpenMP Code

R, Getting Started, How to Run R, Interactive Mode, A First R Session

batch mode, Interactive Mode

first session, A First R Session

interactive mode, How to Run R

snow code, Introducing the snow Package

runs of consecutive ones, finding, Using all() and any()

runtime errors, Syntax and Runtime Errors

S

S (programming language), Introduction

S expression pointers (SEXPs), Running GDB on R Itself

S-Plus (programming language), Introduction

S3 classes, Object-Oriented Programming, Object-Oriented Programming, S3 Classes, Example: OOP in the lm() Linear Model Function, Finding the Implementations of Generic Methods, Using Inheritance, Using Inheritance, Extended Example: A Class for Storing Upper-Triangular Matrices, Implementing a Generic Function on an S4 Class

class for storing upper-triangular matrices example, Using Inheritance

finding implementations of generic methods, Example: OOP in the lm() Linear Model Function

generic functions, S3 Classes

OOP in lm() function example, Object-Oriented Programming

procedure for polynomial regression example, Extended Example: A Class for Storing Upper-Triangular Matrices

using inheritance, Using Inheritance

vs. S4 classes, Implementing a Generic Function on an S4 Class

writing, Finding the Implementations of Generic Methods

S4 classes, Extended Example: A Procedure for Polynomial Regression, S4 Classes, Writing S4 Classes, Implementing a Generic Function on an S4 Class

implementing generic function on, Writing S4 Classes

vs. S3 classes, Implementing a Generic Function on an S4 Class

writing, S4 Classes

salary study, Extended Example: A Salary Study

Salzman, Pete, Debugging

sapply() function, Vector In, Vector Out, Applying Functions to Lists, Extended Example: An Employee Database

applying functions to lists, Applying Functions to Lists

using on data frames, Extended Example: An Employee Database

save() function, saving collection of objects with, Removing Specific Objects with the rm() Function

saving graphs to files, Saving Graphs to Files

scalars, Scalars, Scalars, Vectors, Arrays, and Matrices, Arithmetic and Boolean Operators and Values

Boolean operators, Arithmetic and Boolean Operators and Values

vectors, Scalars, Vectors, Arrays, and Matrices

scan() function, Loops, Accessing the Keyboard and Monitor

scatter/gather paradigm, Introducing the snow Package

schedevnt() function, Extended Example: Discrete-Event Simulation in R, Extended Example: Discrete-Event Simulation in R

scope hierarchy, The Top-Level Environment

sepsoundtone() function, Extended Example: Aids for Learning Chinese Dialects

seq() function, The help() Function, Generating Useful Vectors with the : Operator

serialize() function, Sockets in R

set operations, Set Operations

set.seed() function, Moving Up in the World: More Convenient Debugging Tools

setbreakpoint() function, Calling browser() Directly

setClass() function, S4 Classes

setdiff() set operation, Set Operations

setequal() set operation, Set Operations

setMethod() function, Writing S4 Classes

setting breakpoints, Using Browser Commands, Calling browser() Directly, Calling browser() Directly

calling browser() function directly, Using Browser Commands

using setbreakpoint() function, Calling browser() Directly

setwd() function, Writing to a File

shared-memory systems, Using Multicore Machines, Sources of Overhead

shared-memory/threads model, GPUs, The omp single Pragma

Sherman-Morrison-Woodbury formula, Extended Example: A Procedure for Polynomial Regression

shortcuts, Startup and Shutdown, Startup and Shutdown, If You Don’t Know Quite What You’re Looking For

help() function, Startup and Shutdown

help.search() function, If You Don’t Know Quite What You’re Looking For

showframe() function, Extended Example: A Function to Display the Contents of a Call Frame

sim global variable, When Should You Use Global Variables?

simplifying code, When Should You Use Global Variables?

simulation programming in R, Simulation Programming in R, Simulation Programming in R, Built-In Random Variate Generators, Built-In Random Variate Generators

built-in random variate generators, Simulation Programming in R

combinatorial simulation, Built-In Random Variate Generators

obtaining same random stream in repeated runs, Built-In Random Variate Generators

sin() math function, Math Functions

single brackets, List Indexing

single-server queuing system, Extended Example: Discrete-Event Simulation in R

sink() function, Use of String Utilities in the edtdbg Debugging Tool

slots, S4 class, Writing S4 Classes

snow package, Sockets in R, The Mutual Outlinks Problem, Introducing the snow Package, Running snow Code, Running snow Code, How Much Speedup Can Be Attained?, Extended Example: K-Means Clustering

implementing parallel R, Sockets in R

k-means clustering (KMC), Extended Example: K-Means Clustering

snow code, Introducing the snow Package, Running snow Code, Running snow Code

analyzing, Running snow Code

running, Introducing the snow Package

speedup, How Much Speedup Can Be Attained?

socketConnection() function, Sockets in R

sockets, Overview of TCP/IP

socketSelect() function, Sockets in R

solve() function, Linear Algebra Operations on Vectors and Matrices

sorting, numerical, Functions for Statistical Distributions

sos package, Help for Other Topics

source, installing R from, Installing from a Linux Package Manager

sourceval parameter, mapsound() function, Extended Example: Aids for Learning Chinese Dialects

Spearman rank correlation, Extended Example: A Measure of Association

speed, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Vectorization for Speedup, Extended Example: Generating a Powers Matrix, Extended Example: Avoiding Memory Copy, Byte Code Compilation, Byte Code Compilation

byte code compilation, Byte Code Compilation

finding slow spots in code, Extended Example: Avoiding Memory Copy

for loop, Performance Enhancement: Speed and Memory, Performance Enhancement: Speed and Memory, Vectorization for Speedup, Extended Example: Generating a Powers Matrix

achieving better speed in Monte Carlo simulation example, Vectorization for Speedup

generating powers matrix example, Extended Example: Generating a Powers Matrix

vectorization for speedup, Performance Enhancement: Speed and Memory

writing fast R code, Performance Enhancement: Speed and Memory

Spinu, Vitalie, Debugging Finding City Pairs

split() function, The tapply() Function, Running snow Code

sprintf() function, paste()

sqrt() function, Vector In, Vector Out, Doing Math and Simulations in R

stack trace, Using Browser Commands

startup and shutdown, Extended Example: Regression Analysis of Exam Grades

static task assignment, Embarrassingly Parallel Applications and Those That Aren’t

stationary distributions, Markov chains, Extended Example: Vector Cross Product

statistical distributions, functions for, Calculus

str() function, Lists

string utilities, in edtdbg debugging tool, Extended Example: Forming Filenames

string-manipulation functions, Character Strings, An Overview of String-Manipulation Functions, grep(), grep(), grep(), paste(), paste(), paste(), paste(), regexpr()

gregexpr(), regexpr()

grep(), grep()

nchar(), grep()

paste(), grep()

regexpr(), paste()

sprintf(), paste()

strsplit(), paste()

substr(), paste()

stringsAsFactors argument, data.frame() function, Creating Data Frames

strsplit() function, paste()

subdeterminants, Extended Example: Vector Cross Product

submatrices, assigning values to, Matrix Indexing

subnames argument, subtable() function, Extended Example: Extracting a Subtable

subscripting operations, What’s Considered a Replacement Function?

subset() function, Generating Filtering Indices, More on Treatment of NA Values

subsetting, vector, A First R Session

substr() function, paste()

subtable() function, Extended Example: Extracting a Subtable

suffix, testing filename for given, Regular Expressions

sum() function, Math Functions, Analyzing the snow Code

summary() function, Data Frames, Extended Example: Regression Analysis of Exam Grades

summaryRprof() function, How Rprof() Works

summing contents of many files, Writing to a File

<<- (superassignment operator), Introduction to Functions, No Pointers in R, When Should You Use Global Variables?

simplifying code, When Should You Use Global Variables?

writing to nonlocals with, No Pointers in R

superassignment operator (<<-), Introduction to Functions, No Pointers in R, When Should You Use Global Variables?

simplifying code, When Should You Use Global Variables?

writing to nonlocals with, No Pointers in R

sweep() linear algebra function, Linear Algebra Operations on Vectors and Matrices

symmetric matrix, Extended Example: Finding the Closest Pair of Vertices in a Graph

syntax errors, Syntax and Runtime Errors

T

t() function, Using the apply() Function, Extended Example: Aids for Learning Chinese Dialects, Linear Algebra Operations on Vectors and Matrices

tabdom() function, Extended Example: Extracting a Subtable

tables, Working with Tables, Working with Tables, Matrix/Array-Like Operations on Tables, Extended Example: Extracting a Subtable, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table

extracting subtable example, Matrix/Array-Like Operations on Tables

finding largest cells in, Extended Example: Extracting a Subtable

functions, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table, Extended Example: Finding the Largest Cells in a Table

aggregate(), Extended Example: Finding the Largest Cells in a Table

cut(), Extended Example: Finding the Largest Cells in a Table

matrix/array-like operations, Working with Tables

tags, Creating Lists

tapply() function, Common Functions Used with Factors, The tapply() Function, The split() Function, The split() Function

factors, Common Functions Used with Factors

vs. by() function, The split() Function

vs. split() function, The tapply() Function

tbl argument, subtable() function, Extended Example: Extracting a Subtable

tblarray array, Extended Example: Extracting a Subtable

TCP/IP, Overview of TCP/IP

termination condition, A Quicksort Implementation

testing vector equality, Extended Example: Recoding an Abalone Data Set

text concordance, Adding and Deleting List Elements, Accessing List Components and Values

text editors, Extended Example: A Self-Bookkeeping Vector Class

text files, reading, Reading Text Files

text() function, adding text to graphs with, Adding Points: The points() Function

text, adding to graphs with text() function, Adding Points: The points() Function

threaded code, Extended Example: Discrete-Event Simulation in R

threads, Using Multicore Machines

three-dimensional tables, Working with Tables

Tierney, Luke, The Mutual Outlinks Problem

tocol parameter, mapsound() function, Extended Example: Aids for Learning Chinese Dialects

tools, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Antibugging, Moving Up in the World: More Convenient Debugging Tools

debugging, Antibugging, Moving Up in the World: More Convenient Debugging Tools

for composing function code, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class, Extended Example: A Self-Bookkeeping Vector Class

edit() function, Extended Example: A Self-Bookkeeping Vector Class

text editors and IDEs, Extended Example: A Self-Bookkeeping Vector Class

top-level environment, The Top-Level Environment

trace() function, Tracking with the trace() Function

traceback() function, Tracking with the trace() Function

tracemem() function, Functional Programming and Memory Issues

training set, Extended Example: Predicting Discrete-Valued Time Series

transcendental functions, Vector In, Vector Out

transition probability, Extended Example: Finding Stationary Distributions of Markovv Chains

treelike data structures, Extended Example: A Binary Search Tree

U

u variable, Writing to Nonlocals with the Superassignment Operator

Ubuntu, installing R on, Installing R

unclass() function, “What Is This?”

union() set operation, Set Operations

unlist() function, Extended Example: Text Concordance

unname() function, Accessing List Components and Values

unserialize() function, Sockets in R

upn argument, showframe() function, Extended Example: A Function to Display the Contents of a Call Frame

upper-triangular matrices, class for storing, Using Inheritance

URLs, accessing files on remote machines via, Extended Example: Reading PUMS Census Files

V

values, Vector In, Matrix Out, Using NULL, Matrix Indexing, Matrix Indexing, Extended Example: Text Concordance, More on Treatment of NA Values, Arithmetic and Boolean Operators and Values, Default Values for Arguments

assigning to submatrices, Matrix Indexing

Boolean, Arithmetic and Boolean Operators and Values

list, accessing, Extended Example: Text Concordance

NA, Vector In, Matrix Out, More on Treatment of NA Values

NULL, Using NULL

return, Default Values for Arguments

vanilla option, startup/shutdown, Startup and Shutdown

variable scope, Introduction to Functions

variables, Introduction to Functions, A Vectorized if-then-else: The ifelse() Function, A Vectorized if-then-else: The ifelse() Function, Factors and Tables, Factors and Tables, Extended Example: Discrete-Event Simulation in R

assessing statistical relation of two, A Vectorized if-then-else: The ifelse() Function

categorical, Factors and Tables

global, Introduction to Functions, Extended Example: Discrete-Event Simulation in R

nominal, Factors and Tables

vector assignment issues, Functional Programming and Memory Issues

vector cross product, Linear Algebra Operations on Vectors and Matrices

vector filtering, Vectorization for Speedup

vector functions, Extended Example: Achieving Better Speed in a Monte Carlo Simulation

vector-filtering capability, A Quicksort Implementation

vector/matrix distinction, Extended Example: Finding the Closest Pair of Vertices in a Graph

vectorization, Vectors, Vectors, Performance Enhancement: Speed and Memory

defined, Vectors

for speedup, Performance Enhancement: Speed and Memory

vectorized operations, Vector In, Vector Out

vectors, A First R Session, Vectors, the R Workhorse, Vectors, Scalars, Vectors, Arrays, and Matrices, Scalars, Vectors, Arrays, and Matrices, Scalars, Vectors, Arrays, and Matrices, Obtaining the Length of a Vector, Matrices and Arrays as Vectors, Matrices and Arrays as Vectors, Recycling, Common Vector Operations, Common Vector Operations, Vector Arithmetic and Logical Operations, Vector Indexing, Generating Useful Vectors with the : Operator, Generating Vector Sequences with seq(), Using all() and any(), Using all() and any(), Extended Example: Finding Runs of Consecutive Ones, Extended Example: Predicting Discrete-Valued Time Series, Vectorized Operations, Vector In, Vector Out, Vector In, Matrix Out, Using NULL, Filtering, Filtering, Generating Filtering Indices, Generating Filtering Indices, The Selection Function which(), A Vectorized if-then-else: The ifelse() Function, Extended Example: A Measure of Association, Extended Example: Recoding an Abalone Data Set, Vector Element Names, Vector Element Names, Sorting, Sorting

all() and any() functions, Using all() and any(), Using all() and any(), Extended Example: Finding Runs of Consecutive Ones

finding runs of consecutive ones example, Using all() and any()

predicting discrete-valued time series example, Extended Example: Finding Runs of Consecutive Ones

c() function, Vector Element Names

common operations, Common Vector Operations, Common Vector Operations, Vector Arithmetic and Logical Operations, Vector Indexing, Generating Useful Vectors with the : Operator, Generating Vector Sequences with seq()

arithmetic and logical operations, Common Vector Operations

colon operator (:), Vector Indexing

generating vector sequences with seq() function, Generating Useful Vectors with the : Operator

repeating vector constants with rep() function, Generating Vector Sequences with seq()

vector indexing, Vector Arithmetic and Logical Operations

computing inner product of two, Sorting

declarations, Matrices and Arrays as Vectors

defined, A First R Session

elements, Scalars, Vectors, Arrays, and Matrices, Scalars, Vectors, Arrays, and Matrices, Vector Element Names

adding and deleting, Scalars, Vectors, Arrays, and Matrices

naming, Vector Element Names

filtering, Filtering, Filtering, Generating Filtering Indices, Generating Filtering Indices

generating indices for, Filtering

with subset() function, Generating Filtering Indices

with which() function, Generating Filtering Indices

ifelse() function, The Selection Function which(), A Vectorized if-then-else: The ifelse() Function, Extended Example: A Measure of Association

assessing statistical relation of two variables example, A Vectorized if-then-else: The ifelse() Function

recoding abalone data set example, Extended Example: A Measure of Association

linear algebra operations on, Sorting

matrices and arrays as, Matrices and Arrays as Vectors

NA value, Vector In, Matrix Out

NULL value, Using NULL

obtaining length of, Obtaining the Length of a Vector

recycling, Recycling

scalars, Scalars, Vectors, Arrays, and Matrices

testing vector equality, Extended Example: Recoding an Abalone Data Set

vectorized operations, Extended Example: Predicting Discrete-Valued Time Series, Vectorized Operations, Vector In, Vector Out

vector in, matrix out, Vector In, Vector Out

vector in, vector out, Vectorized Operations

vertices, graph, finding, Changing the Size of a Matrix

W

Web, downloading packages from, Package Basics, Package Basics, Installing Packages Automatically

installing automatically, Package Basics

installing manually, Installing Packages Automatically

where browser command, Using Browser Commands

which() function, Generating Filtering Indices

which.max() function, Extended Example: Finding Outliers, Math Functions

which.min() function, Math Functions

whitespace, Using the scan() Function

Wickham, Hadley, Extended Example: Finding the Largest Cells in a Table

wireframe() function, Creating Three-Dimensional Plots

wmins matrix, Extended Example: Finding the Closest Pair of Vertices in a Graph

workers, snow package, Introducing the snow Package

working directory, Startup and Shutdown

write.table() function, Writing to a File

writeBin() function, Sockets in R

writeLines() function, Sockets in R

writing, No Pointers in R, No Pointers in R, Writing to Nonlocals with assign(), Writing to Nonlocals with assign(), Extended Example: Discrete-Event Simulation in R, Extended Example: Discrete-Event Simulation in R, When Should You Use Global Variables?, The edit() Function, Finding the Implementations of Generic Methods, S4 Classes, Writing to a File, Writing to a File, Interfacing R to Other Languages, Writing C/C++ Functions to Be Called from R, Example: Extracting Subdiagonals from a Square Matrix, Debugging R/C Code, Debugging R/C Code

binary operations, The edit() Function

C/C++ functions to be called from R, Interfacing R to Other Languages, Writing C/C++ Functions to Be Called from R, Example: Extracting Subdiagonals from a Square Matrix, Debugging R/C Code, Debugging R/C Code

compiling and running code, Example: Extracting Subdiagonals from a Square Matrix

debugging R/C code, Debugging R/C Code

extracting subdiagonals from square matrix example, Writing C/C++ Functions to Be Called from R

prediction of discrete-valued time series example, Debugging R/C Code

closures, When Should You Use Global Variables?

discrete-event simulation in R example, Extended Example: Discrete-Event Simulation in R

getting files and directory information, Writing to a File

S3 classes, Finding the Implementations of Generic Methods

S4 classes, S4 Classes

summing contents of many files example, Writing to a File

to nonlocals, No Pointers in R, Writing to Nonlocals with assign(), Writing to Nonlocals with assign()

with assign() function, Writing to Nonlocals with assign()

with superassignment operator, No Pointers in R

when to use global variables, Extended Example: Discrete-Event Simulation in R

X

x variable, Writing to Nonlocals with the Superassignment Operator

xlim option, Changing Character Sizes: The cex Option

Y

ylim option, Changing Character Sizes: The cex Option

Z

z variable, Writing to Nonlocals with the Superassignment Operator